Data is being generated and processed at an exponentially increasing rate. However, this increased rate of data generation and processing can result in many errors or inefficiencies arising during the generation and processing of that data. Unfortunately, these errors or inefficiencies can be difficult to identify due to the sheer amount of data involved.
There exists a need for techniques to integrate a large volume of data and analyze it to reliably determine errors or inefficiencies associated with the generation and processing of all that data. The identification of these errors or inefficiencies can be used in order to improve the accuracy and efficiency in generating and processing future data.